Spatially resolved environmental fate models: A review

Space-specific flux estimation of atmospheric chemicals from point sources to soil

Predicting chemical flux to soil from industrial point sources accurately at a regional scale has been a significant challenge due to high uncertainty in spatial heterogeneity and quantification. To address this challenge, we developed an innovative approach by combining California Air Resources Board Puff (CALPUFF) and mass balance models, leveraging their complementary strengths in quantitative accuracy and spatial precision. Specifically, CALPUFF was used to predict the polycyclic aromatic hydrocarbons (PAHs) flux to soil due to industrial sources. Additionally, the spatial distribution coefficient of PAHs flux (e.g., si for spatial unit i) was calculated by neural network and combined with the mass balance model to obtain the results of total PAHs fluxes, which were then combined with the results predicted by CALPUFF to effectively estimate the contribution of industrial sources to soil PAHs flux. Taking a petrochemical industry region located in Zhejiang province, China as a case study, results showed the input Phenanthrene (Phe) and Benzo(a)pyrene (BaP) fluxes predicted by CALPUFF were generally lower than those by the mass balance model, with slightly different distribution patterns. CALPUFF results, based on 36 industrial sources, partially represent those of the mass balance model, which includes all sources and pathways. It was suggested that industrial sources contributed 49%-89% and 65%-100% of soil Phe and BaP, respectively across the study area. The average Phe flux from point sources by deposition averaged 2.68 mg m-2∙a-1 in 2021, accounting for approximately 60% of the total Phe flux to soil. The average BaP flux from point sources by deposition averaged 0.0755 mg m-2∙a-1, accounting for only 0.1%-3.65% of the total BaP flux to soil. Thereby, our approach fills up a gap between the relevance to point sources and the accuracy of deposition quantification in estimating chemical flux from specific point sources to soil at a regional scale.

Water, Water Everywhere, but Every Drop Unique: Challenges in the Science to Understand the Role of Contaminants of Emerging Concern in the Management of Drinking Water Supplies

The protection and management of water resources continues to be challenged by multiple and ongoing factors such as shifts in demographic, social, economic, and public health requirements. Physical limitations placed on access to potable supplies include natural and human-caused factors such as aquifer depletion, aging infrastructure, saltwater intrusion, floods, and drought. These factors, although varying in magnitude, spatial extent, and timing, can exacerbate the potential for contaminants of concern (CECs) to be present in sources of drinking water, infrastructure, premise plumbing and associated tap water. This monograph examines how current and emerging scientific efforts and technologies increase our understanding of the range of CECs and drinking water issues facing current and future populations. It is not intended to be read in one sitting, but is instead a starting point for scientists wanting to learn more about the issues surrounding CECs. This text discusses the topical evolution CECs over time (Section 1), improvements in measuring chemical and microbial CECs, through both analysis of concentration and toxicity (Section 2) and modeling CEC exposure and fate (Section 3), forms of treatment effective at removing chemical and microbial CECs (Section 4), and potential for human health impacts from exposure to CECs (Section 5). The paper concludes with how changes to water quantity, both scarcity and surpluses, could affect water quality (Section 6). Taken together, these sections document the past 25 years of CEC research and the regulatory response to these contaminants, the current work to identify and monitor CECs and mitigate exposure, and the challenges facing the future.

Meteorological data source comparison-a case study in geospatial modeling of potential environmental exposure to abandoned uranium mine sites in the Navajo Nation

Meteorological (MET) data is a crucial input for environmental exposure models. While modeling exposure potential using geospatial technology is a common practice, existing studies infrequently evaluate the impact of input MET data on the level of uncertainty on output results. The objective of this study is to determine the effect of various MET data sources on the potential exposure susceptibility predictions. Three sources of wind data are compared: The North American Regional Reanalysis (NARR) database, meteorological aerodrome reports (METARs) from regional airports, and data from local MET weather stations. These data sources are used as inputs into a machine learning (ML) driven GIS Multi-Criteria Decision Analysis (GIS-MCDA) geospatial model to predict potential exposure to abandoned uranium mine sites in the Navajo Nation. Results indicate significant variations in results derived from different wind data sources. After validating the results from each source using the National Uranium Resource Evaluation (NURE) database in a geographically weighted regression (GWR), METARs data combined with the local MET weather station data showed the highest accuracy, with an average R2 of 0.74. We conclude that local direct measurement-based data (METARs and MET data) produce a more accurate prediction than the other sources evaluated in the study. This study has the potential to inform future data collection methods, leading to more accurate predictions and better-informed policy decisions surrounding environmental exposure susceptibility and risk assessment.

Assessment of factors affecting the diurnal variations of atmospheric PAHs based on a numerical simulation

Atmospheric polycyclic aromatic hydrocarbons (PAHs) are a type of organic pollutants that seriously endanger human health. Obtaining the diurnal variations of PAHs and clarifying their impact mechanisms are significant for the government to formulate targeted prevention and control measures. However, the influencing factors that dominate the diurnal variations of common PAHs are currently unclear. In order to solve this problem, 16 PAHs selected by the United States Environmental Protection Agency (EPA) as priority-controlled pollutants were simulated with high resolution. The simulation results were validated based on diurnal observations in the vertical direction. Although the model underestimated the particle-phase concentrations of most components, it captured their diurnal variations fairly well. In addition, we assessed the factors affecting the diurnal variations of PAHs with sensitivity tests, including chemical reactions and atmospheric diffusion. The results showed that the transforming ratios of PAHs by oxidants were higher during the day than that at night due to the dominant reactions with OH radical. Atmospheric dispersion affected the vertical distribution of PAHs, which resulted in higher day/night ratios at high altitudes than near the ground. We also compared the strength of atmospheric diffusion and chemical reaction on the diurnal trends of PAHs. Near the ground, atmospheric diffusion was the most dominant factor in determining their diurnal trends. At high altitudes, their diurnal trends were determined by a combination of atmospheric diffusion and chemical reactions. These findings can provide a comprehensive understanding of the diurnal variations of common PAHs, which are informative for the prevention and control of PAHs pollution.

Predicting the regional contamination evolution of DDT for 100-years with a new gridded spatial and dynamic multimedia fate model

In 1996 high dichlorodiphenyltrichloroethane (DDT) concentrations were found in Lake Maggiore (Italy) fish and sediments. DDT was produced by a chemical company located in a subalpine valley (Ossola valley, Piedmont Region, Italy), and ended up in the Toce River, a tributary of Lake Maggiore. In the area surrounding the chemical plant, high DDT concentrations in soil and vegetation were found after subsequent investigations. The quantification of the release from contaminated soil and the following migration toward downwind areas, deposition to the soil, and further evaporation plays an important role in understanding future DDT trends in soil and the atmosphere. To study this phenomenon, soil, and vegetation from Ossola Valley were monitored in 2001 and 2011. The concentration values obtained (soils: 0.05 to 1 μg/g; vegetation 2-100 ng/g), allowed to reconstruct the contamination gradient in the valley and were used to develop and calibrate a spatially resolved multimedia fugacity model. The model accounts for spatial and temporal dynamicity of environmental characteristics such as wind speed and direction, variable air compartment height etc., and simulates the fate and transport of chemicals on a local scale. The dynamic emission of DDT (about 13,000 kg for the 50 y production time) to the air was estimated and utilized for a 100-year simulation (from 1948 to 2048). The results obtained allowed to understand the temporal and spatial pattern of DDT contamination for a long period at a local scale as well as the potential contribution as a source potentially affecting sites at larger distances.

Atmospheric Modelling of Mercury in the Southern Hemisphere and Future Research Needs: A Review

Mercury is a toxic pollutant that can negatively impact the population’s health and the environment. The research on atmospheric mercury is of critical concern because of the diverse process that this pollutant suffers in the atmosphere as well as its deposition capacity, which can provoke diverse health issues. The Minamata Convention encourages the protection of the adverse effects of mercury, where research is a part of the strategies and atmospheric modelling plays a critical role in achieving the proposed aim. This paper reviews the study of modelling atmospheric mercury based on the southern hemisphere (SH). The article discusses diverse aspects focused on the SH such as the spatial distribution of mercury, its emissions projections, interhemispheric transport, and deposition. There has been a discrepancy between the observed and the simulated values, especially concerning the seasonality of gaseous elemental mercury and total gaseous mercury. Further, there is a lack of research about the emissions projections in the SH and mercury deposition, which generates uncertainty regarding future global scenarios. More studies on atmospheric mercury behaviour are imperative to better understand the SH’s mercury cycle.

Local Scale Exposure and Fate of Engineered Nanomaterials

Nanotechnology is a growing megatrend in industrial production and innovations. Many applications utilize engineered nanomaterials (ENMs) that are potentially released into the atmospheric environment, e.g., via direct stack emissions from production facilities. Limited information exists on adverse effects such ENM releases may have on human health and the environment. Previous exposure modeling approaches have focused on large regional compartments, into which the released ENMs are evenly mixed. However, due to the localization of the ENM release and removal processes, potentially higher airborne concentrations and deposition fluxes are obtained around the production facilities. Therefore, we compare the ENM concentrations from a dispersion model to those from the uniformly mixed compartment approach. For realistic release scenarios, we based the modeling on the case study measurement data from two TiO2 nanomaterial handling facilities. In addition, we calculated the distances, at which 50% of the ENMs are deposited, serving as a physically relevant metric to separate the local scale from the regional scale, thus indicating the size of the high exposure and risk region near the facility. As a result, we suggest a local scale compartment to be implemented in the multicompartment nanomaterial exposure models. We also present a computational tool for local exposure assessment that could be included to regulatory guidance and existing risk governance networks.